[R-sig-Geo] [FORGED] different models

Virginia Morera Pujol morera.virginia at gmail.com
Thu Apr 7 09:52:14 CEST 2016

Hi Rolf,

Thank you for your very complete response. If I understand it correctly
then, I should just include the Cartesian coordinates in my covariates list
if I want to model the intensity specifically in relation to them as well
as the covariates, correct?

Oh, and just for clarification, I do not name my point patterns "ppp" and
my covariates "covariate" (although I kind of like the idea of calling my
dog "dog"). I was just trying to make a general example, but thanks for the
heads up anyway!


Virginia Morera
PhD Student
Department of Animal Biology
University of Barcelona

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2016-04-07 5:11 GMT+02:00 Rolf Turner <r.turner at auckland.ac.nz>:

> On 06/04/16 22:00, Virginia Morera Pujol wrote:
>> Hi all,
>> This might be a very dumb question that shows I have very little idea of
>> what I am talking about, but I'll risk it:
>> What is the difference between fitting a model using these 3 different
>> syntaxes?
>> 1/ fit1 <- ppm(ppp, ~covariate),
>> 2/ fit2 <- ppm(ppp, ~x+y+Z, covariates=list(Z=covariate))
>> 3/ fit3 <- ppm(ppp, ~x+y+covariate)
>> where ppp is my point pattern and "covariate" is a pixel image? I realise
>> the outputs of 2 and 3 are the same and different to that of 1, so I guess
>> the question really is
>> a/ Is there any difference, practical or in the actual computations of the
>> model, between using 2 and 3?
>> b/ What is the difference between (2&3) and 1?
> (1) There is essentially no difference between fits 2 & 3.  The fit 2
> syntax is provided so that the user can have the relevant covariates
> bundled up in a list without any need to extract these covariates from that
> list.   With the fit 2 syntax you don't need to have all covariates present
> in your workspace.
> E.g.: fit <- ppm(bei ~ elev + grad, data=bei.extra)
> (2) The fit 2 syntax is essentially the same as that used by lm() and
> glm() and was designed in imitation thereof.
> (3) The preferred structure of a call to ppm() is
>     fit2 <- ppm(ppp ~ x + y + Z, data=list(Z=covariate))
> Note:  "data" rather than "covariates"; no comma between the name of the
> response variable ("ppp") and the formula.
> This makes the syntax identical to that of lm() and glm().
> The syntax that you used is a remnant of earlier versions of spatstat and
> remains acceptable for reasons of backward compatibility.
> (4) The difference between model 1 and models 2 and 3 is that models 2 and
> 3 involve the Cartesian coordinates "x" and "y".  Model 1 is such that the
> model intensity takes the form
>    exp(beta_0 + beta_1 * covariate)
> In models 2 and 3 the model intensity takes the (more complex) form
>    exp(beta_0 + beta_1 * x + beta_2 *y beta_3 * covariate)
> Note that "x" and "y" are *reserved* names.  You cannot use these names
> for any covariates *other than* the Cartesian coordinates.
> (5) The name "covariate" is probably *not* a good name for a covariate.
> As fortune(77) puts it "Would you call your dog 'dog'?"
> (6) Likewise (and even more so) "ppp" is *not* a good name for a point
> pattern, since it clashes the name of the creator function ppp().
> cheers,
> Rolf Turner
> --
> Technical Editor ANZJS
> Department of Statistics
> University of Auckland
> Phone: +64-9-373-7599 ext. 88276

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